Optimal sizing of energy storage for community microgrids considering building thermal dynamics

This paper proposes an optimization model for the sizing of energy storage for community microgrids considering the building thermal dynamics and customer comfort preference. The proposed model minimizes the annualized cost of the community microgrid, including energy storage investment, purchased energy cost, demand charge, energy storage degradation cost, voluntary load shedding cost, and the cost associated with customer discomfort due to room temperature deviation. The decision variables are the power and energy capacity of invested energy storage. In particular, heating, ventilation and air-conditioning (HVAC) systems are assumed to be scheduled intelligently by the microgrid central controller while maintaining the indoor temperature in the comfort range set by customers. For this purpose, the detailed thermal dynamic characteristics of buildings has been integrated into the optimization model. Numerical simulations show significant cost reduction with the proposed model. The impacts of various costs on the optimal solution are investigated through sensitivity analysis.